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README.md
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* **Language Identification (LID):** Token-wise classification of Hindi, English, and other linguistic units.<br>
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Initial predictions were generated using the [Microsoft LID tool](https://github.com/microsoft/LID-tool), which annotators then reviewed and corrected.
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* **Matrix Language Identification (MLI):** Sentence-level annotation of the dominant language.
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Example
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"किसानों को अपनी फसल बेचने में दिक्कत न हो इसके लिये Electronic National Agriculture Market यानि ई-नाम योजना तेजी से काम हो रहा है।" Tagged Language: Hindi
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"India’s automation and design expert pool is vast, और ज़्यादातर Global companies के इंजीिनयिंरग center भी भारत में हैं।" Tagged Language: English
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```
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* **Part-of-Speech (POS) Tagging:** Syntactic categorization for linguistic analysis.<br>
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Tags were pre-assigned using the [CodeSwitch NLP library](https://github.com/sagorbrur/codeswitch), which annotators then reviewed and corrected.
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* **Named Entity Recognition (NER):** Identification of entities in Hinglish text.<br>
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Each token is pre-assigned a language tag using the [CodeSwitch NLP library](https://github.com/sagorbrur/codeswitch), which annotators then reviewed and corrected.
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Example
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"मालूम हो कि पेरिस स्थित Financial Action Task Force, FATF ने जून 2018 में पाकिस्तान को ग्रे लिस्ट में रखा था।"
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NER tags: "पेरिस": GPE, "Financial Action Task Force, FATF": ORGANISATION, "2018": Date, "पाकिस्तान": GPE
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```
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* **Translation:** Parallel translation of sentences in Romanized Hindi and Devanagari Hindi and English languages.<br>
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* **Language Identification (LID):** Token-wise classification of Hindi, English, and other linguistic units.<br>
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Initial predictions were generated using the [Microsoft LID tool](https://github.com/microsoft/LID-tool), which annotators then reviewed and corrected.
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```
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Example:
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sentence: प्रधानमंत्री नरेन्द्र मोदी डिजिटल इंडिया मिशन को आगे बढ़ाने के लिए पिछले सप्ताह Google के CEO सुंदर पिचाई से मुलाकात की थी।
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LID tags: hi hi hi en en en hi hi hi hi hi hi hi en hi en hi hi hi hi hi hi
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```
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* **Matrix Language Identification (MLI):** Sentence-level annotation of the dominant language.
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```
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Example:
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sentence:"किसानों को अपनी फसल बेचने में दिक्कत न हो इसके लिये Electronic National Agriculture Market यानि ई-नाम योजना तेजी से काम हो रहा है।" Tagged Language: Hindi
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sentence:"India’s automation and design expert pool is vast, और ज़्यादातर Global companies के इंजीिनयिंरग center भी भारत में हैं।" Tagged Language: English
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```
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* **Part-of-Speech (POS) Tagging:** Syntactic categorization for linguistic analysis.<br>
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Tags were pre-assigned using the [CodeSwitch NLP library](https://github.com/sagorbrur/codeswitch), which annotators then reviewed and corrected.
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```
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Example:
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sentence: भारत द्वारा बनाया गया Unified Payments Interface यानि UPI भारत की एक बहुत बड़ी success story है ।
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POS tags: PROPN ADP VERB VERB PROPN PROPN PROPN CONJ PROPN PROPN ADP DET ADJ ADJ NOUN NOUN VERB X
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```
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* **Named Entity Recognition (NER):** Identification of entities in Hinglish text.<br>
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Each token is pre-assigned a language tag using the [CodeSwitch NLP library](https://github.com/sagorbrur/codeswitch), which annotators then reviewed and corrected.
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```
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Example:
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sentence: "मालूम हो कि पेरिस स्थित Financial Action Task Force, FATF ने जून 2018 में पाकिस्तान को ग्रे लिस्ट में रखा था।"
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NER tags: "पेरिस": GPE, "Financial Action Task Force, FATF": ORGANISATION, "2018": Date, "पाकिस्तान": GPE
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```
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* **Translation:** Parallel translation of sentences in Romanized Hindi and Devanagari Hindi and English languages.<br>
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